Prevalence of Pathological Gambling in Quebec in 2002
Bibliographic record
Abstract
OBJECTIVE: To assess gambling behaviours and the problems associated with pathological gambling among the adult population of Quebec in 2002. METHOD: In Phase 1 of this 2-phase study, a total sample of 8842 adults was assessed. We used the South Oaks Gambling Screen (SOGS), adapted for telephone interview, to assess one-half of the sample; the other one-half was evaluated with the Canadian Problem Gambling Index (CPGI). In the study's second phase, we compared the classifications obtained from these screening instruments with classifications obtained by a psychologist using a semistructured clinical telephone interview. RESULTS: The results indicate that the prevalence of pathological gambling in 2002 (at which time 0.8% of the adult population were classified as probable pathological gamblers) did not differ from the proportion obtained in 1996 (1.0%), despite the significant decrease in gambling participation in 2002 (81% vs 90% in 1996). The most popular gambling activities were buying lottery tickets (68%), participating in fundraising draws (40%), gambling in casinos (18%), playing cards with family or with friends (10%), playing bingo (9%), and playing video lotteries (8%). The findings obtained from the SOGS and the CPGI revealed that the 2 instruments perform similarly when identifying pathological gambling prevalence. However, the results of the semistructured clinical telephone interviews differed from the results obtained with the screening instruments: 82% of the gamblers initially identified as probable pathological gamblers by the SOGS or the CPGI were not confirmed by a clinical interview. CONCLUSION: The discrepancy between the results of the screening questionnaires and the clinical evaluation is significant, and this difference needs to be addressed before further cross-sectional or longitudinal studies are conducted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".